A task scheduling algorithm considering bandwidth competition in cloud computing

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8223 LNCS, Issue , 2013, Pages 270-280

  Zhang, Jie ^a   Zhu, Xudong ^a   Ying, Bishan ^b  

^a ZHEJIANG GONGSHANG UNIVERSITY   (China)

^b WASU Media and Network Co Ltd   (China)

Author keywords

Cloud computing; Scheduling; Workflow

Indexed keywords

BANDWIDTH SCHEDULING; CLOUD ENVIRONMENTS; DYNAMIC BANDWIDTH; NETWORK BANDWIDTH; SCHEDULE ALGORITHMS; TASK-SCHEDULING ALGORITHMS; WORKFLOW; WORKFLOW SCHEDULING;

BANDWIDTH; CLOUD COMPUTING; INTERNET; SCHEDULING; SIMULATED ANNEALING;

COMPUTER SYSTEMS;

EID: 84893781847     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-41428-2_22     Document Type: Conference Paper

References (14)

1. Deelman, E., Blythe, J., Gil, Y., Kesselman, C.: Workflow Management in GriPhyN. The Grid Resource Management. Kluwer, Netherlands (2003)
2. Ranganathan, K., Foster, I.: Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications. In: 11th IEEE International Symposium on High Performance Distributed Computing (2002)
3. Blythe, J., et al.: Task Scheduling Strategies for Workflow-based Applications in Grids. In: IEEE International Symposium on Cluster Computing and Grid, CCGrid (2005)
4. Ullman, J.D.: NP-complete Scheduling Problems. Journal of Computer and System Sciences 10, 384-393 (1975)
5. Jia, Y., Buyya, R., Ramamohanaro, K.: Workflow schdeduling algorithms for Grid computing. Metaheuristics for scheduling in distributed computing environments. Springer, Berlin (2008)
6. van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow Patterns. Technical Report, Eindhoven University of Technology (2000)
7. van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Advanced Workflow Patterns. In: Scheuermann, P., Etzion, O. (eds.) CoopIS 2000. LNCS, vol. 1901, pp. 18-29. Springer, Heidelberg (2000)
8. van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow Patterns (December 2004), http://tmitwww.tm.tue.nl/research/ patterns/
9. Yang, T., Gerasoulis, A.: aDSC: Scheduling Parallel Tasks on an Unbounded Number of Processors. IEEE Trans. Parallel and Distributed Systems 5(9), 951-967 (1994)
10. Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing. IEEE Transactions on Parallel and Distributed Systems 13(3), 260-274 (2002)
11. Aarts, E.H.L., Korst, J.H.M.: Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Computing. Wiley, Chichester (1989)
12. Bouleimen, K., Lecocq, H.: A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research 149, 268-281 (2003)
13. Kwok, Y., Ahmad, I.: Dynamic Critical-Path Schduling: An Effective Technique for Allocating Task Graphs to Multiprocessors. IEEE Trans. Parallel and Distributed Systems 7(5), 506-521 (1996)
14. Kwok, Y., Ahmad, I.: Benchmarking and Comparison of the Task Graph Scheduling Algorithms. Joumal of Parallel and Distributed Computing 59(3), 351-422 (1999)